Samuel Jenness
Assistant Professor, Department of Epidemiology - Rollins School of Public Health
Emory University
CSDE Research Areas:
- Demographic Measurements and Methods
- Health of People and Populations
In the News:
- Jenness and Co-authors Study Social Contact Networks in an Urban Jail to Understand Infectious Disease Transmission (06/12/2024)
- New Infographic on Reducing HIV in the Southern U.S. is Developed from Research by Hamilton, Jenness, and Goodreau (02/08/2024)
- Jenness and Co-authors Use Social Contact Data to Examine COVID-19 Transmission (11/17/2023)
- Hamilton, Jenness, and Goodreau Examine the Potential Contribution of PrEP Uptake by Adolescents (11/17/2023)
- Jenness and Goodreau Awarded Funding from the NIMH (03/04/2022)
- CSDE Welcomes Four New External Affiliates! (10/22/2021)
Samuel Jenness is an infectious disease epidemiologist specializing in mathematical and computational approaches for studying the drivers of and prevention strategies for infectious disease through the framework of dynamic transmission networks.
As an Assistant Professor in the Department of Epidemiology at the Rollins School of Public Health of Emory University, Jenness leads the EpiModel Research Lab and also collaborates on several projects in both methods and applications for infectious disease epidemiology.
Jenness's methodological research focuses on the development of an open-source software platform for epidemic modeling, EpiModel, which allows users to build, simulate, and analyze complex mechanistic models for transmission of arbitrarily defined infectious disease systems. EpiModel provides a powerful toolkit for modeling dynamic contact networks that are often fundamental for representing transmission of diseases requiring direct contact. EpiModel has been used in over 50 scientific publications, both by his group and modeling researchers around the world!
Jenness's applied research focuses on the epidemiology of HIV, sexually transmitted infections, and other infectious diseases. He is interested in how we can use mechanistic modeling and network science frameworks to understand the drivers of these diseases, and to design and evaluate effective prevention strategies. Recent applications have used models to simulate the co-circulation of multiple co-circulating pathogens within the same population, since the risk factors for acquiring one disease may depend on the epidemic dynamics of other infections transmitted along the same contact network.
More broadly, the work of Jenness's EpiModel Research Lab involves addressing these questions with research in the following domains:
- Infectious disease epidemiology
- Mechanistic/mathematical modeling of infectious disease
- Network science
- Causal inference methods for epidemiology
- Survey research design and analysis
- Computational epidemiology & scientific software development